Hazard assessment at Mount Etna using a hybrid lava flow inundation model and satellite-based land classification

被引:0
|
作者
Andrew J. L. Harris
Massimiliano Favalli
Robert Wright
Harold Garbeil
机构
[1] Clermont Université,Laboratoire Magmas et Volcans
[2] Université Blaise Pascal,undefined
[3] Istituto Nazionale di Geofisica e Vulcanologia—Pisa,undefined
[4] HIGP/SOEST,undefined
[5] University of Hawai’i,undefined
来源
Natural Hazards | 2011年 / 58卷
关键词
Lava flow; Risk; FLOWGO; ASTER image; Land classification; Mt. Etna;
D O I
暂无
中图分类号
学科分类号
摘要
Using a lava flow emplacement model and a satellite-based land cover classification, we produce a map to allow assessment of the type and quantity of natural, agricultural and urban land cover at risk from lava flow invasion. The first step is to produce lava effusion rate contours, i.e., lines linking distances down a volcano’s flank that a lava flow will likely extend if fed at a given effusion rate from a predetermined vent zone. This involves first identifying a vent mask and then running a downhill flow path model from the edge of every pixel around the vent mask perimeter to the edge of the DEM. To do this, we run a stochastic model whereby the flow path is projected 1,000 times from every pixel around the vent mask perimeter with random noise being added to the DEM with each run so that a slightly different flow path is generated with each run. The FLOWGO lava flow model is then run down each path, at a series of effusion rates, to determine likely run-out distance for channel-fed flow extending down each path. These results are used to plot effusion rate contours. Finally, effusion rate contours are projected onto a land classification map (produced from an ASTER image of Etna) to assess the type and amount of each land cover class falling within each contour. The resulting maps are designed to provide a quick look-up capability to assess the type of land at risk from lava extending from any location at a range of likely effusion rates. For our first (2,000 m) vent zone case used for Etna, we find a total of area of ~680 km2 is at risk from flows fed at 40 m3 s−1, of which ~6 km2 is urban, ~150 km2 is agriculture and ~270 km2 is grass/woodland. The model can also be run for specific cases, where we find that Etna’s 1669 vent location, if active today, would likely inundate almost 11 km2 of urban land, as well as 15.6 km2 of agricultural land, including 9.5 km2 of olive groves and 5.2 km2 of vineyards and fruit/nut orchards.
引用
收藏
页码:1001 / 1027
页数:26
相关论文
共 43 条
  • [31] A hybrid colour model based land cover classification using random forest and support vector machine classifiers
    Rama, M. Christy
    Mahendran, D. S.
    Kumar, T. C. Raja
    [J]. INTERNATIONAL JOURNAL OF APPLIED PATTERN RECOGNITION, 2018, 5 (02) : 87 - 100
  • [32] On the ability of RegCM4 regional climate model to simulate surface solar radiation patterns over Europe: an assessment using satellite-based observations
    Alexandri, G.
    Georgoulias, A. K.
    Zanis, P.
    Katragkou, E.
    Tsikerdekis, A.
    Kourtidis, K.
    Meleti, C.
    [J]. ATMOSPHERIC CHEMISTRY AND PHYSICS, 2015, 15 (22) : 13195 - 13216
  • [33] Accuracy Assessment of Land-Use Land-Cover Classification Using Semantic Segmentation-Based Deep Learning Model and RapidEye Imagery
    Sim, Woodam
    Yim, Jong Su
    Lee, Jung-Soo
    [J]. KOREAN JOURNAL OF REMOTE SENSING, 2023, 39 (03) : 269 - 282
  • [34] Hydrological model using ground- and satellite-based data for river flow simulation towards supporting water resource management in the Red River Basin, Vietnam
    Nguyen Hoang Hiep
    Nguyen Duc Luong
    Tran Thi Viet Nga
    Bui Thi Hieu
    Ung Thi Thuy Ha
    Bui Du Duong
    Vu Duc Long
    Hossain, Faisal
    Lee, Hyongki
    [J]. JOURNAL OF ENVIRONMENTAL MANAGEMENT, 2018, 217 : 346 - 355
  • [35] Assessment of spatio-temporal trends of satellite-based aerosol optical depth using Mann-Kendall test and Sen's slope estimator model
    Mohammad, Lal
    Mondal, Ismail
    Bandyopadhyay, Jatisankar
    Pham, Quoc Bao
    Nguyen, Xuan Cuong
    Dinh, Cham Dao
    Al-Quraishi, Ayad M. Fadhil
    [J]. GEOMATICS NATURAL HAZARDS & RISK, 2022, 13 (01) : 1270 - 1298
  • [36] A vision-based hole quality assessment technique for robotic drilling of composite materials using a hybrid classification model
    Stephen K. H. Lee
    Alexej Simeth
    Eoin P. Hinchy
    Peter Plapper
    Noel P. O’Dowd
    Conor T. McCarthy
    [J]. The International Journal of Advanced Manufacturing Technology, 2023, 129 : 1249 - 1258
  • [37] A vision-based hole quality assessment technique for robotic drilling of composite materials using a hybrid classification model
    Lee, Stephen K. H.
    Simeth, Alexej
    Hinchy, Eoin P.
    Plapper, Peter
    O'Dowd, Noel P.
    McCarthy, Conor T.
    [J]. INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY, 2023, 129 (3-4): : 1249 - 1258
  • [38] Modification and application of the satellite-based land data assimilation scheme for very dry soil regions using AMSR-E images: Model validation for Mongolia - a CEOP data platform
    Mahadevan, Pathmathevan
    Koike, Toshio
    Fujii, Hideyuki
    Tamagawa, Katsunori
    Li, Xin
    Kaihotsu, Ichirow
    [J]. JOURNAL OF THE METEOROLOGICAL SOCIETY OF JAPAN, 2007, 85A : 243 - 260
  • [39] Hazard zoning for spatial planning using GIS-based landslide susceptibility assessment: a new hybrid integrated data-driven and knowledge-based model
    Qadir Ashournejad
    Ali Hosseini
    Biswajeet Pradhan
    Seyed Javad Hosseini
    [J]. Arabian Journal of Geosciences, 2019, 12
  • [40] Hazard zoning for spatial planning using GIS-based landslide susceptibility assessment: a new hybrid integrated data-driven and knowledge-based model
    Ashournejad, Qadir
    Hosseini, Ali
    Pradhan, Biswajeet
    Hosseini, Seyed Javad
    [J]. ARABIAN JOURNAL OF GEOSCIENCES, 2019, 12 (04)